jupyter-notebook

问题 I have an example from a data science book I am trying to run in a Jupyter notebook. The code sippet looks like this from sklearn.gaussian_process import GaussianProcess # define the model and draw some data model = lambda x: x * np.sin(x) xdata = np.array([1, 3, 5, 6, 8]) ydata = model(xdata) # Compute the Gaussian process fit gp = GaussianProcess(corr='cubic', theta0=1e-2, thetaL=1e-4, thetaU=1E-1, random_start=100) gp.fit(xdata[:, np.newaxis], ydata) xfit = np.linspace(0, 10, 1000) yfit,

问题 I have an example from a data science book I am trying to run in a Jupyter notebook. The code sippet looks like this from sklearn.gaussian_process import GaussianProcess # define the model and draw some data model = lambda x: x * np.sin(x) xdata = np.array([1, 3, 5, 6, 8]) ydata = model(xdata) # Compute the Gaussian process fit gp = GaussianProcess(corr='cubic', theta0=1e-2, thetaL=1e-4, thetaU=1E-1, random_start=100) gp.fit(xdata[:, np.newaxis], ydata) xfit = np.linspace(0, 10, 1000) yfit,

问题 I have an example from a data science book I am trying to run in a Jupyter notebook. The code sippet looks like this from sklearn.gaussian_process import GaussianProcess # define the model and draw some data model = lambda x: x * np.sin(x) xdata = np.array([1, 3, 5, 6, 8]) ydata = model(xdata) # Compute the Gaussian process fit gp = GaussianProcess(corr='cubic', theta0=1e-2, thetaL=1e-4, thetaU=1E-1, random_start=100) gp.fit(xdata[:, np.newaxis], ydata) xfit = np.linspace(0, 10, 1000) yfit,

问题 So after installing VSCode and Python 3.7.4 (64 bit) I really struggle to make the "python interactive" work. I have installed the Python extension in VScode, also jupyter and jupyter-lab but I keep getting the error "Exception: Jupyter command jupyter-notebook not found." when I try to run a cell/a line. I am running Windows 10, using pip3 回答1: What did the trick was, that a few packages were outdated. Firstly I had to uninstall pyzmq and install it again. Then I ran pip3 install --upgrade

问题 I am trying to run matlab code from Jupyter notebooks. I am following the link below for guidance: https://www.youtube.com/watch?v=WufMGW5Bv4g Now I have installed matlab_kernel. And I see that it is installed on the machine when i run a pip list . When I open Jupyter notebook, and click on the New notebook dropdown, I do not see the MATLAB option. Also, at point 3:22, the instructor installs python from Program Files/Matlab. However, I do not see the MATLAB folder in my Program Files. What

问题 I installed tensorflow 2 on my mac using conda according these instructions: conda create -n tf2 tensorflow Then I installed ipykernel to add this new environment to my jupyter notebook kernels as follows: conda activate tf2 conda install ipykernel python -m ipykernel install --user --name=tf2 That seemed to work well, I am able to see my tf2 environment on my jupyter notebook kernels. Then I tried to run the simple MNIST example to check if all was working properly and I when I execute this

问题 I installed tensorflow 2 on my mac using conda according these instructions: conda create -n tf2 tensorflow Then I installed ipykernel to add this new environment to my jupyter notebook kernels as follows: conda activate tf2 conda install ipykernel python -m ipykernel install --user --name=tf2 That seemed to work well, I am able to see my tf2 environment on my jupyter notebook kernels. Then I tried to run the simple MNIST example to check if all was working properly and I when I execute this

问题 I am graphing the number of occurrences that a value occurs in two different datasets. One plot (plot 1) graphs perfectly, the bars are right above the numbers on the x-axis. On the second plot (plot 2), there should be two bars, one above the 1 x-axis value and the other above the 2 x-axis value, but both bars are thick and squashed between 1 and 2on the x-axis. How do I get the second graph to look like the first graph? This is the code that I used in Jupyter notebook to generate both plots

问题 I am graphing the number of occurrences that a value occurs in two different datasets. One plot (plot 1) graphs perfectly, the bars are right above the numbers on the x-axis. On the second plot (plot 2), there should be two bars, one above the 1 x-axis value and the other above the 2 x-axis value, but both bars are thick and squashed between 1 and 2on the x-axis. How do I get the second graph to look like the first graph? This is the code that I used in Jupyter notebook to generate both plots

问题 I'm trying to scroll through some magnetic resonance slices using plt.show() and ipywidgets interact() function. I've found no problem by slowly moving the slider, but an important delay is found when sliding through the slices a little bit faster. Here below is the code I'm using. def dicom_animation(x, volume): fig = plt.figure(figsize=(8,8)) plt.imshow(volume['slices'][x]['pixel_array'], cmap=plt.cm.gray) interact(dicom_animation, volume = fixed(a), x=IntSlider(round(len(a['slices'])/2,0),